1. Field of the Invention
The present invention relates to a shape descriptor extracting method, and more particularly, to a shape descriptor extracting method based on an image skeleton. The present invention is based on Korean Patent Application No. 2000-62163 which is incorporated herein by reference.
2. Description of the Related Art
A shape descriptor is based on a lower abstraction level description enabling an automatic extraction, and is a basic descriptor which humans can perceive from an image. Algorithms, which describe the shape of a specific object within an image and measure the degree of matching or similarity based on the shape, are studied. However, the algorithms only describe the shapes of the specific objects, so that there are many problems in perceiving the shapes of general objects. Currently, shape descriptors, suggested by a standard group, such as MPEG-7, are obtained by looking for features through various transformations of the given objects to solve the above problem.
There are many kinds of shape descriptors. Two shape descriptors adopted in eXperimental Model 1 (XM) of MPEG-7 are known as a Zernike moment shape descriptor and a curvature scale space shape descriptor.
As for the Zernike moment shape descriptor, Zernike basis functions are defined for a variety of shapes to investigate the shape of an object within an image. Then, the image of fixed size is projected over the basis functions, and the resultant values are used as the shape descriptors.
As for the curvature scale space descriptor, the contour of a model image is extracted, and changes of curvature points along the contour are expressed on a scaled space. Then, the locations with respect to the peak values are expressed as a z-dimensional vector. However, to extract the former descriptor, the sizes of input images are restricted. Meanwhile, to extract the latter shape descriptor, the extracted shape must be only one object.